Applying unmixing to gene expression data for tumor phylogeny inference

<p>Abstract</p> <p>Background</p> <p>While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall into a relatively small number of "sub-types," each characterized a roughly equivalent sequence of mutations by which it progresses in different patients. There is currently great interest in identifying the common sub-types and applying them to the development of diagnostics or therapeutics. Phylogenetic methods have shown great promise for inferring common patterns of tumor progression, but suffer from limits of the technologies available for assaying differences between and within tumors. One approach to tumor phylogenetics uses differences between single cells within tumors, gaining valuable information about intra-tumor heterogeneity but allowing only a few markers per cell. An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity.</p> <p>Results</p> <p>The present work applies "unmixing" methods, which separate complex data sets into combinations of simpler components, to attempt to gain advantages of both tissue-wide and single-cell approaches to cancer phylogenetics. We develop an unmixing method to infer recurring cell states from microarray measurements of tumor populations and use the inferred mixtures of states in individual tumors to identify possible evolutionary relationships among tumor cells. Validation on simulated data shows the method can accurately separate small numbers of cell states and infer phylogenetic relationships among them. Application to a lung cancer dataset shows that the method can identify cell states corresponding to common lung tumor types and suggest possible evolutionary relationships among them that show good correspondence with our current understanding of lung tumor development.</p> <p>Conclusions</p> <p>Unmixing methods provide a way to make use of both intra-tumor heterogeneity and large probe sets for tumor phylogeny inference, establishing a new avenue towards the construction of detailed, accurate portraits of common tumor sub-types and the mechanisms by which they develop. These reconstructions are likely to have future value in discovering and diagnosing novel cancer sub-types and in identifying targets for therapeutic development.</p

Reproducibility of measurements of potential doubling time of tumour cells in the multicentre National Cancer Institute protocol T92-0045

We compared the flow cytometric measurement and analysis of the potential doubling time (Tpot) between three centres involved in the National Cancer Institute (NCI) protocol T92-0045. The primary purpose was to understand and minimize the variation within the measurement. A total of 102 specimens were selected at random from patients entered into the trial. Samples were prepared, stained, run and analysed in each centre and a single set of data analysed by all three centres. Analysis of the disc data set revealed that the measurement of labelling index (LI) was robust and reproducible. The estimation of duration of S-phase (Ts) was subject to errors of profile interpretation, particularly DNA ploidy status, and analysis. The LI dominated the variation in Tpot such that the level of final agreement, after removal of outliers and ploidy agreement, reached correlation coefficients of 0.9. The sample data showed poor agreement within each of the components of the measurement. There was some improvement when ploidy was in agreement, but correlation coefficients failed to exceed values of 0.5 for Tpot. The data suggest that observer-associated analysis of Ts and tissue processing and tumour heterogeneity were the major causes of variability in the Tpot measurement. The first two aspects can be standardized and minimized, but heterogeneity will remain a problem with biopsy techniques. © 1999 Cancer Research Campaig

Exploiting Clinical Trial Data Drastically Narrows the Window of Possible Solutions to the Problem of Clinical Adaptation of a Multiscale Cancer Model

The development of computational models for simulating tumor growth and response to treatment has gained significant momentum during the last few decades. At the dawn of the era of personalized medicine, providing insight into complex mechanisms involved in cancer and contributing to patient-specific therapy optimization constitute particularly inspiring pursuits. The in silico oncology community is facing the great challenge of effectively translating simulation models into clinical practice, which presupposes a thorough sensitivity analysis, adaptation and validation process based on real clinical data. In this paper, the behavior of a clinically-oriented, multiscale model of solid tumor response to chemotherapy is investigated, using the paradigm of nephroblastoma response to preoperative chemotherapy in the context of the SIOP/GPOH clinical trial. A sorting of the model's parameters according to the magnitude of their effect on the output has unveiled the relative importance of the corresponding biological mechanisms; major impact on the result of therapy is credited to the oxygenation and nutrient availability status of the tumor and the balance between the symmetric and asymmetric modes of stem cell division. The effect of a number of parameter combinations on the extent of chemotherapy-induced tumor shrinkage and on the tumor's growth rate are discussed. A real clinical case of nephroblastoma has served as a proof of principle study case, demonstrating the basics of an ongoing clinical adaptation and validation process. By using clinical data in conjunction with plausible values of model parameters, an excellent fit of the model to the available medical data of the selected nephroblastoma case has been achieved, in terms of both volume reduction and histological constitution of the tumor. In this context, the exploitation of multiscale clinical data drastically narrows the window of possible solutions to the clinical adaptation problem

Machine learning-based prediction of breast cancer growth rate in-vivo

BackgroundDetermining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.MethodsA serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.ResultsSM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.ConclusionOur Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications

Increasing genome instability in adrenocortical carcinoma progression with involvement of chromosomes 3, 9 and X at the adenoma stage

The investigation of chromosomal aberrations in adrenocortical tumours has been limited by the difficulties of applying classical cytogenetics to tumours with low levels of proliferation. We have therefore applied the technique of interphase cytogenetics to paraffin-embedded archival specimens of 14 adrenocortical adenomas and 13 carcinomas. Hybridizations were performed using centromere-specific probes to chromosomes 3, 4, 9, 17, 18 and X, which have been shown to be altered in other types of tumours. Chromosomal imbalance was defined on the basis of changes in both chromosome index (CI) and signal distribution (SD). Where only one of these was altered, this was classified as a tendency to gain or loss. On the basis of the analysis of optimal hybridizations, carcinomas showed gains in all chromosomes studied, five of nine showing gains in multiple chromosomes. Gains were most common in chromosomes 3, 9 and, in particular X, eight of 11 showing gain, and one a tendency to gain. Chromosomal gain was seen less commonly in adenomas, but again chromosomes 3, 9 and X were involved. Losses were infrequent, only one carcinoma showing loss of chromosome 18, and adenomas showing a tendency to loss of chromosomes 4 (two cases), 17 (one case) and 18 (two cases). Our data suggest that changes in chromosomes 3, 9 and X are early events in adrenocortical tumorigenesis, and that there is increasing chromosomal instability with tumour progression. © 1999 Cancer Research Campaig

Effect of ploidy, recruitment, environmental factors, and tamoxifen treatment on the expression of sigma-2 receptors in proliferating and quiescent tumour cells

Recently, we demonstrated that sigma-2 receptors may have the potential to be a biomarker of tumour cell proliferation (Mach et al (1997) Cancer Res57: 156–161). If sigma-2 receptors were a biomarker of tumour cell proliferation, they would be amenable to detection by non-invasive imaging procedures, thus eliminating many of the problems associated with the flow cytometric measures of tumour cell proliferation presently used in the clinic. To be a good biomarker of tumour cell proliferation, the expression of sigma-2 receptors must be essentially independent of many of the biological, physiological, and/or environmental properties that are found in solid tumours. In the investigation reported here, the mouse mammary adenocarcinoma lines, 66 (diploid) and 67 (aneuploid), 9L rat brain tumour cells, and MCF-7 human breast tumour cells were used to study the extent and kinetics of expression of sigma-2 receptors in proliferative (P) and quiescent (Q) tumour cells as a function of species, cell type, ploidy, pH, nutrient depletion, metabolic state, recruitment from the Q-cell compartment to the P-cell compartment, and treatment with tamoxifen. In these experiments, the expression of sigma-2 receptors solely reflected the proliferative status of the tumour cells. None of the biological, physiological, or environmental properties that were investigated had a measurable effect on the expression of sigma-2 receptors in these model systems. Consequently, these data suggest that the proliferative status of tumours and normal tissues can be non-invasively assessed using radiolabelled ligands that selectively bind sigma-2 receptors. © 1999 Cancer Research Campaig

Progressive Telomere Dysfunction Causes Cytokinesis Failure and Leads to the Accumulation of Polyploid Cells

Most cancer cells accumulate genomic abnormalities at a remarkably rapid rate, as they are unable to maintain their chromosome structure and number. Excessively short telomeres, a known source of chromosome instability, are observed in early human-cancer lesions. Besides telomere dysfunction, it has been suggested that a transient phase of polyploidization, in most cases tetraploidization, has a causative role in cancer. Proliferation of tetraploids can gradually generate subtetraploid lineages of unstable cells that might fire the carcinogenic process by promoting further aneuploidy and genomic instability. Given the significance of telomere dysfunction and tetraploidy in the early stages of carcinogenesis, we investigated whether there is a connection between these two important promoters of chromosomal instability. We report that human mammary epithelial cells exhibiting progressive telomere dysfunction, in a pRb deficient and wild-type p53 background, fail to complete the cytoplasmatic cell division due to the persistence of chromatin bridges in the midzone. Flow cytometry together with fluorescence in situ hybridization demonstrated an accumulation of binucleated polyploid cells upon serial passaging cells. Restoration of telomere function through hTERT transduction, which lessens the formation of anaphase bridges by recapping the chromosome ends, rescued the polyploid phenotype. Live-cell imaging revealed that these polyploid cells emerged after abortive cytokinesis due to the persistence of anaphase bridges with large intervening chromatin in the cleavage plane. In agreement with a primary role of anaphase bridge intermediates in the polyploidization process, treatment of HMEC-hTERT cells with bleomycin, which produces chromatin bridges through illegimitate repair, resulted in tetraploid binucleated cells. Taken together, we demonstrate that human epithelial cells exhibiting physiological telomere dysfunction engender tetraploid cells through interference of anaphase bridges with the completion of cytokinesis. These observations shed light on the mechanisms operating during the initial stages of human carcinogenesis, as they provide a link between progressive telomere dysfunction and tetraploidy

CDH1 promoter hypermethylation and E-cadherin protein expression in infiltrating breast cancer

BACKGROUND: The E-cadherin gene (CDH1) maps, at chromosome 16q22.1, a region often associated with loss of heterozygosity (LOH) in human breast cancer. LOH at this site is thought to lead to loss of function of this tumor suppressor gene and was correlated with decreased disease-free survival, poor prognosis, and metastasis. Differential CpG island methylation in the promoter region of the CDH1 gene might be an alternative way for the loss of expression and function of E-cadherin, leading to loss of tissue integrity, an essential step in tumor progression. METHODS: The aim of our study was to assess, by Methylation-Specific Polymerase Chain Reaction (MSP), the methylation pattern of the CDH1 gene and its possible correlation with the expression of E-cadherin and other standard immunohistochemical parameters (Her-2, ER, PgR, p53, and K-67) in a series of 79 primary breast cancers (71 infiltrating ductal, 5 infiltrating lobular, 1 metaplastic, 1 apocrine, and 1 papillary carcinoma). RESULTS: CDH1 hypermethylation was observed in 72% of the cases including 52/71 ductal, 4/5 lobular carcinomas and 1 apocrine carcinoma. Reduced levels of E-cadherin protein were observed in 85% of our samples. Although not statistically significant, the levels of E-cadherin expression tended to diminish with the CDH1 promoter region methylation. In the group of 71 ductal cancinomas, most of the cases of showing CDH1 hypermethylation also presented reduced levels of expression of ER and PgR proteins, and a possible association was observed between CDH1 methylation and ER expression (p = 0.0301, Fisher's exact test). However, this finding was not considered significant after Bonferroni correction of p-value. CONCLUSION: Our preliminary findings suggested that abnormal CDH1 methylation occurs in high frequencies in infiltrating breast cancers associated with a decrease in E-cadherin expression in a subgroup of cases characterized by loss of expression of other important genes to the mammary carcinogenesis process, probably due to the disruption of the mechanism of maintenance of DNA methylation in tumoral cells

Enhanced Proliferation of Monolayer Cultures of Embryonic Stem (ES) Cell-Derived Cardiomyocytes Following Acute Loss of Retinoblastoma

Background: Cardiomyocyte (CM) cell cycle analysis has been impeded because of a reliance on primary neonatal cultures of poorly proliferating cells or chronic transgenic animal models with innate compensatory mechanisms. Methodology/Principal Findings: We describe an in vitro model consisting of monolayer cultures of highly proliferative embryonic stem (ES) cell-derived CM. Following induction with ascorbate and selection with puromycin, early CM cultures are.98 % pure, and at least 85 % of the cells actively proliferate. During the proliferative stage, cells express high levels of E2F3a, B-Myb and phosphorylated forms of retinoblastoma (Rb), but with continued cultivation, cells stop dividing and mature functionally. This developmental transition is characterized by a switch from slow skeletal to cardiac TnI, an increase in binucleation, cardiac calsequestrin and hypophosphorylated Rb, a decrease in E2F3, B-Myb and atrial natriuretic factor, and the establishment of a more negative resting membrane potential. Although previous publications suggested that Rb was not necessary for cell cycle control in heart, we find following acute knockdown of Rb that this factor actively regulates progression through the G1 checkpoint and that its loss promotes proliferation at the expense of CM maturation. Conclusions/Significance: We have established a unique model system for studying cardiac cell cycle progression, and show in contrast to previous reports that Rb actively regulates both cell cycle progression through the G1 checkpoint an